Pub Date : 2018-10-01DOI: 10.4018/IJEOE.2018100105
M. Naderi, E. Khamehchi
This article describes how the accurate estimation of the rate of penetration (ROP) is essential to minimize drilling costs. There are various factors influencing ROP such as formation rock, drilling fluid properties, wellbore geometry, type of bit, hydraulics, weight on bit, flow rate and bit rotation speed. This paper presents two novel methods based on least square support vector machine (LSSVM) and genetic programming (GP). Models are a function of depth, weight on bit, rotation speed, stand pipe pressure, flow rate, mud weight, bit rotational hours, plastic viscosity, yield point, 10 second gel strength, 10 minute gel strength, and fluid loss. Results show that LSSVM estimates 92% of field data with average absolute relative error of less than 6%. In addition, sensitivity analysis showed that factors of depth, weight on bit, stand pipe pressure, flow rate and bit rotation speed account for 93% of total variation of ROP. Finally, results indicate that LSSVM is superior over GP in terms of average relative error, average absolute relative error, root mean square error, and the coefficient of determination.
{"title":"Application of Optimized Least Square Support Vector Machine and Genetic Programming for Accurate Estimation of Drilling Rate of Penetration","authors":"M. Naderi, E. Khamehchi","doi":"10.4018/IJEOE.2018100105","DOIUrl":"https://doi.org/10.4018/IJEOE.2018100105","url":null,"abstract":"This article describes how the accurate estimation of the rate of penetration (ROP) is essential to minimize drilling costs. There are various factors influencing ROP such as formation rock, drilling fluid properties, wellbore geometry, type of bit, hydraulics, weight on bit, flow rate and bit rotation speed. This paper presents two novel methods based on least square support vector machine (LSSVM) and genetic programming (GP). Models are a function of depth, weight on bit, rotation speed, stand pipe pressure, flow rate, mud weight, bit rotational hours, plastic viscosity, yield point, 10 second gel strength, 10 minute gel strength, and fluid loss. Results show that LSSVM estimates 92% of field data with average absolute relative error of less than 6%. In addition, sensitivity analysis showed that factors of depth, weight on bit, stand pipe pressure, flow rate and bit rotation speed account for 93% of total variation of ROP. Finally, results indicate that LSSVM is superior over GP in terms of average relative error, average absolute relative error, root mean square error, and the coefficient of determination.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133958880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.4018/IJEOE.2018100103
Hiba Yahyaoui, A. Dekdouk, S. Krichen
This article addresses the distribution network reconfiguration problem (DNRP) and the power flow method. The studied DNRP operates on standard configurations of electrical networks. The main objectives handled are the minimization of power loss, the number of switching operations and the deviations of bus voltages from their rated values. Metaheuristic approaches based on Greedy Iterated Local Search where proposed to solve the DNRP. A benchmarking testbed on standard systems well illustrates the incentive behind using GrILS for solving the DNRP. In addition, the proposed approaches and the power flow method where implemented on GPU architecture. The GPU implementation shows its effectiveness against the CPU in terms of time consuming specially for large-scale bus systems.
{"title":"GPU-Based Power Flow Method a Multi-Objective Power Optimization Model for Reconfiguration Problem in Radial Distribution Networks","authors":"Hiba Yahyaoui, A. Dekdouk, S. Krichen","doi":"10.4018/IJEOE.2018100103","DOIUrl":"https://doi.org/10.4018/IJEOE.2018100103","url":null,"abstract":"This article addresses the distribution network reconfiguration problem (DNRP) and the power flow method. The studied DNRP operates on standard configurations of electrical networks. The main objectives handled are the minimization of power loss, the number of switching operations and the deviations of bus voltages from their rated values. Metaheuristic approaches based on Greedy Iterated Local Search where proposed to solve the DNRP. A benchmarking testbed on standard systems well illustrates the incentive behind using GrILS for solving the DNRP. In addition, the proposed approaches and the power flow method where implemented on GPU architecture. The GPU implementation shows its effectiveness against the CPU in terms of time consuming specially for large-scale bus systems.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133263181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.4018/IJEOE.2018070103
Tejasvi Kothapalli
Reducing power usage in the residential sector is a global problem. Appliances used for space heating, cooling, and lighting are the primary sources of home energy consumption, increased costs, and CO2 emissions. Such devices are a significant source of energy wastage if they are left on and not being used. This article proposes a solution to reduce energy wastage in smart homes. The solution consists of a method to detect the presence of resident activities in the household based on Wi-Fi devices. It presents a model for identifying the Wi-Fi devices that are similar in usage compared to the resident's appliances using machine learning techniques. In addition to displaying the device usage charts, this solution helps in automatically turning off such appliances when they are not in use. A controlled experiment is conducted to evaluate the performance of the solution. The results indicate that this approach can significantly reduce energy wastage in the homes.
{"title":"Saving Energy in Homes Using Wi-Fi Device Usage Patterns","authors":"Tejasvi Kothapalli","doi":"10.4018/IJEOE.2018070103","DOIUrl":"https://doi.org/10.4018/IJEOE.2018070103","url":null,"abstract":"Reducing power usage in the residential sector is a global problem. Appliances used for space heating, cooling, and lighting are the primary sources of home energy consumption, increased costs, and CO2 emissions. Such devices are a significant source of energy wastage if they are left on and not being used. This article proposes a solution to reduce energy wastage in smart homes. The solution consists of a method to detect the presence of resident activities in the household based on Wi-Fi devices. It presents a model for identifying the Wi-Fi devices that are similar in usage compared to the resident's appliances using machine learning techniques. In addition to displaying the device usage charts, this solution helps in automatically turning off such appliances when they are not in use. A controlled experiment is conducted to evaluate the performance of the solution. The results indicate that this approach can significantly reduce energy wastage in the homes.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"3 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131450896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.4018/IJEOE.2018070101
Alireza Heidari, M. Moradi, A. Aslani, A. Hajinezhad
Micro-grids are the key technologies known to solve challenges such as increased electric demand, fatigue electric installations, electrical leakage and pressures and opposition from environmental advocacy groups. The current article is presenting an improved optimization algorithm based on a differential evolution algorithm to achieve the optimal response for managing distributed energy resources in micro-grids. The simulation results show that: 1) The final cost of network management in systems based on the agent is very favorable compared to a network regardless of the agent and also are economically much more useful and effective in coordinating various energy sources. 2) The results of the proposed algorithm are much better in comparison with the results of the Fireflies optimization algorithm, a differential evolution algorithm and the particle swarm algorithm. This comparison proves the high performance of the algorithm.
{"title":"Optimization of Micro-Grid Electricity Market Based on Multi Agent Modeling Approach","authors":"Alireza Heidari, M. Moradi, A. Aslani, A. Hajinezhad","doi":"10.4018/IJEOE.2018070101","DOIUrl":"https://doi.org/10.4018/IJEOE.2018070101","url":null,"abstract":"Micro-grids are the key technologies known to solve challenges such as increased electric demand, fatigue electric installations, electrical leakage and pressures and opposition from environmental advocacy groups. The current article is presenting an improved optimization algorithm based on a differential evolution algorithm to achieve the optimal response for managing distributed energy resources in micro-grids. The simulation results show that: 1) The final cost of network management in systems based on the agent is very favorable compared to a network regardless of the agent and also are economically much more useful and effective in coordinating various energy sources. 2) The results of the proposed algorithm are much better in comparison with the results of the Fireflies optimization algorithm, a differential evolution algorithm and the particle swarm algorithm. This comparison proves the high performance of the algorithm.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129812882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.4018/IJEOE.2018070105
Sadaf Karkoodi, A. Aslani, M. Talebi, Soheil Roumi, A. Abbassi
This article describes the limitations and the environmental effects of fossil fuels have provided the drive to create replacement strategies, such as the utilization of renewable energy resources. Solar energy and related technologies are also among fast-growing renewable resources and technologies. Despite different research on solar technologies, an extensive research on the effects of different parts of the collector, such as an absorber, glass cover, and the air gap has not conducted in the warm climate in the Middle East. This article focuses on an unsteady and three-dimensional simulation of a flat plate solar collector considering Discrete Transfer Radiation Model (DTRM). The parameters effecting on efficiency of collector such as the absorber material, tilt angle of the collector and effect of double glazing are analyzed. The result of the numerical analysis shows parameters effecting on collector efficiency, and double-glazed glass.
{"title":"Transient 3D: Simulation of a Flat Plate Solar Collector in a Mild Climate Condition","authors":"Sadaf Karkoodi, A. Aslani, M. Talebi, Soheil Roumi, A. Abbassi","doi":"10.4018/IJEOE.2018070105","DOIUrl":"https://doi.org/10.4018/IJEOE.2018070105","url":null,"abstract":"This article describes the limitations and the environmental effects of fossil fuels have provided the drive to create replacement strategies, such as the utilization of renewable energy resources. Solar energy and related technologies are also among fast-growing renewable resources and technologies. Despite different research on solar technologies, an extensive research on the effects of different parts of the collector, such as an absorber, glass cover, and the air gap has not conducted in the warm climate in the Middle East. This article focuses on an unsteady and three-dimensional simulation of a flat plate solar collector considering Discrete Transfer Radiation Model (DTRM). The parameters effecting on efficiency of collector such as the absorber material, tilt angle of the collector and effect of double glazing are analyzed. The result of the numerical analysis shows parameters effecting on collector efficiency, and double-glazed glass.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128047670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.4018/IJEOE.2018070102
S. Paul, P. Roy
In this article, an Oppositional Differential search algorithm (ODSA) is comprehensively developed and successfully applied for the optimal design of power system stabilizer (PSS) parameters which are added to the excitation system to dampen low frequency oscillation as it pertains to large power system. The effectiveness of the proposed method is examined and validated on a single machine infinite bus (SMIB) using the Heffron-Phillips model. The most important advantage of the proposed method is as it reaches toward the optimal solution without the optimal tuning of input parameters of the ODSA algorithm. In order to verify the effectiveness, the simulation was made for a wide range of loading conditions. The simulation results of the proposed ODSA are compared with those obtained by other techniques available in the recent literature to demonstrate the feasibility of the proposed algorithm.
{"title":"Optimal Design of Power System Stabilizer Using a Novel Evolutionary Algorithm","authors":"S. Paul, P. Roy","doi":"10.4018/IJEOE.2018070102","DOIUrl":"https://doi.org/10.4018/IJEOE.2018070102","url":null,"abstract":"In this article, an Oppositional Differential search algorithm (ODSA) is comprehensively developed and successfully applied for the optimal design of power system stabilizer (PSS) parameters which are added to the excitation system to dampen low frequency oscillation as it pertains to large power system. The effectiveness of the proposed method is examined and validated on a single machine infinite bus (SMIB) using the Heffron-Phillips model. The most important advantage of the proposed method is as it reaches toward the optimal solution without the optimal tuning of input parameters of the ODSA algorithm. In order to verify the effectiveness, the simulation was made for a wide range of loading conditions. The simulation results of the proposed ODSA are compared with those obtained by other techniques available in the recent literature to demonstrate the feasibility of the proposed algorithm.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116620276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.4018/IJEOE.2018070104
O. Samuel, T. E. Boye, A. Ojelade
This article describes how the high energy consumption associated with glass factories has been responsible for high cost of manufacturing of glass. However, there is a need for a systematic approach to assess energy consumption in the factory in order to avoid wastage. Previous methods of assessment could not take into cognizance of assessing the entire unit. Additionally, the methods are mostly complex and not straight forward"To overcome these constraints, an approach for audit energy consumption was developed. Energy study was conducted in a glass production plant in Ughelli, Nigeria to determine the energy requirements for the production of glass. The energy consumption patterns of the units operations were evaluated for production of 200 tonnes of glass bottles. The analysis revealed that there were ten defined units in a glass production. The electrical, thermal and manual energy required for the productions were 84.31, 15.59 and 0.10% of the total energy, respectively. The average energy intensity was estimated to be 818.53 MJ/tonne. The most energy intensive operation was identified as the melting process of the furnace with an energy intensity of 395.94 MJ/tonne, which accounts for 48.37% of the total energy required for glass production. Improvement on the design of the melting furnace is suggested to make the system more energy efficient.
{"title":"Preliminary Energy Assessment of Glass Production in Nigeria","authors":"O. Samuel, T. E. Boye, A. Ojelade","doi":"10.4018/IJEOE.2018070104","DOIUrl":"https://doi.org/10.4018/IJEOE.2018070104","url":null,"abstract":"This article describes how the high energy consumption associated with glass factories has been responsible for high cost of manufacturing of glass. However, there is a need for a systematic approach to assess energy consumption in the factory in order to avoid wastage. Previous methods of assessment could not take into cognizance of assessing the entire unit. Additionally, the methods are mostly complex and not straight forward\"To overcome these constraints, an approach for audit energy consumption was developed. Energy study was conducted in a glass production plant in Ughelli, Nigeria to determine the energy requirements for the production of glass. The energy consumption patterns of the units operations were evaluated for production of 200 tonnes of glass bottles. The analysis revealed that there were ten defined units in a glass production. The electrical, thermal and manual energy required for the productions were 84.31, 15.59 and 0.10% of the total energy, respectively. The average energy intensity was estimated to be 818.53 MJ/tonne. The most energy intensive operation was identified as the melting process of the furnace with an energy intensity of 395.94 MJ/tonne, which accounts for 48.37% of the total energy required for glass production. Improvement on the design of the melting furnace is suggested to make the system more energy efficient.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125029460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-01DOI: 10.4018/IJEOE.2018040101
S. K. Injeti, T. V. Kumar
{"title":"A WDO Framework for Optimal Deployment of DGs and DSCs in a Radial Distribution System Under Daily Load Pattern to Improve Techno-Economic Benefits","authors":"S. K. Injeti, T. V. Kumar","doi":"10.4018/IJEOE.2018040101","DOIUrl":"https://doi.org/10.4018/IJEOE.2018040101","url":null,"abstract":"","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128124675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-01DOI: 10.4018/IJEOE.2018040104
T. Ganesan, M. Aris, P. Vasant
{"title":"Extreme Value Metaheuristics for Optimizing a Many-Objective Gas Turbine System","authors":"T. Ganesan, M. Aris, P. Vasant","doi":"10.4018/IJEOE.2018040104","DOIUrl":"https://doi.org/10.4018/IJEOE.2018040104","url":null,"abstract":"","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121092724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Numerical Study of Discharged Heat Water Effect on Aquatic Environment From Coastal Thermal Power Plant by Using Two Water Discharged Pipes","authors":"A. Issakhov","doi":"10.4018/IJEOE.2018040105","DOIUrl":"https://doi.org/10.4018/IJEOE.2018040105","url":null,"abstract":"Thearticlepresentsanumericalstudyofthethermalloadontheaquaticenvironmentbyusingtwo waterdischargepipesundervariousoperationalcapacitiesofthermalpowerplant.Itissolvedbythe Navier-Stokesandtemperaturetransportequationsforanincompressiblefluidinastratifiedmedium. Theaimofthisarticleistoimprovetheexistingwaterdischargesystemforreducetheheatload onthereservoir-coolerofthethermalpowerplantsoperation(EkibastuzSDPP-1).Inthisarticle, thermalpollutionusingonlytwowaterdischargepipes,usingtheexistingoneandbuildingonlyone additionalintheeasternpartofthereservoir-coolerisnumericallysimulated.Thenumericalmethodis basedontheprojectionmethod,whichwasapproximatedbythefinitevolumemethod.Theobtained numericalresultsofthree-dimensionalstratifiedturbulentflowfortwowaterdischargepipesunder variousoperationalcapacitiesofthethermalpowerplantwerecomparedwithexperimentaldataand withthenumericalresultsforonewaterdischargepipe. KEyWORDS 5-Step Runge-Kutta Method, Ekibastuz SDPP-1, Navier-Stokes Equation, Operational Capacities of Thermal Power Plant, Stratified Medium, Thermal Discharge, Two Water Discharge Pipes","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132098909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}